from sklearn_benchmarks.report import Reporting, ReportingHpo, print_time_report, print_env_info
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
scikit-learn vs. scikit-learn-intelex (Intel® oneAPI) benchmarks: perfect hyperparameters match¶print_time_report()
sklearnex_KMeans_short: 0h 0m 2s
sklearnex_Ridge: 0h 0m 2s
KMeans_short: 0h 0m 3s
sklearnex_LogisticRegression: 0h 0m 6s
sklearnex_KMeans_tall: 0h 0m 11s
Ridge: 0h 0m 12s
KMeans_tall: 0h 0m 28s
LogisticRegression: 0h 0m 28s
sklearnex_KNeighborsClassifier_kd_tree: 0h 0m 37s
KNeighborsClassifier_kd_tree: 0h 2m 54s
xgboost: 0h 5m 1s
catboost_symmetric: 0h 5m 7s
catboost_lossguide: 0h 5m 9s
lightgbm: 0h 5m 18s
HistGradientBoostingClassifier: 0h 5m 29s
sklearnex_KNeighborsClassifier: 0h 6m 28s
KNeighborsClassifier: 0h 28m 25s
total: 1h 6m 7s
print_env_info()
{
"system_info": {
"python": "3.8.10 | packaged by conda-forge | (default, May 11 2021, 07:01:05) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.8.0-1036-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1.3",
"setuptools": "49.6.0.post20210108",
"sklearn": "1.0.dev0",
"numpy": "1.21.0",
"scipy": "1.7.0",
"Cython": null,
"pandas": "1.3.0",
"matplotlib": "3.4.2",
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.15.so",
"prefix": "libopenblas",
"user_api": "blas",
"internal_api": "openblas",
"version": "0.3.15",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/python3.8/site-packages/scikit_learn.libs/libgomp-f7e03b3e.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}
reporting = Reporting(config="config.yml")
reporting.run()
KNeighborsClassifier: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.188 | 0.0 | 4.254 | 0.0 | 1 | 1 | NaN | NaN | 0.571 | 0.0 | 0.330 | 0.0 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.180 | 0.0 | 4.450 | 0.0 | -1 | 5 | NaN | NaN | 0.575 | 0.0 | 0.313 | 0.0 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.158 | 0.0 | 5.057 | 0.0 | -1 | 1 | NaN | NaN | 0.606 | 0.0 | 0.261 | 0.0 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.150 | 0.0 | 5.334 | 0.0 | 1 | 5 | NaN | NaN | 0.558 | 0.0 | 0.269 | 0.0 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.157 | 0.0 | 5.109 | 0.0 | -1 | 100 | NaN | NaN | 0.574 | 0.0 | 0.273 | 0.0 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.192 | 0.0 | 4.176 | 0.0 | 1 | 100 | NaN | NaN | 0.575 | 0.0 | 0.333 | 0.0 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.064 | 0.0 | 0.249 | 0.0 | 1 | 1 | NaN | NaN | 0.123 | 0.0 | 0.523 | 0.0 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.069 | 0.0 | 0.232 | 0.0 | -1 | 5 | NaN | NaN | 0.122 | 0.0 | 0.566 | 0.0 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.067 | 0.0 | 0.239 | 0.0 | -1 | 1 | NaN | NaN | 0.112 | 0.0 | 0.595 | 0.0 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.067 | 0.0 | 0.239 | 0.0 | 1 | 5 | NaN | NaN | 0.121 | 0.0 | 0.553 | 0.0 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.060 | 0.0 | 0.267 | 0.0 | -1 | 100 | NaN | NaN | 0.119 | 0.0 | 0.503 | 0.0 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.071 | 0.0 | 0.226 | 0.0 | 1 | 100 | NaN | NaN | 0.111 | 0.0 | 0.638 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 19.433 | 0.209 | 0.0 | 0.019 | 1 | 1 | 0.712 | 0.949 | 4.659 | 0.038 | 4.171 | 0.056 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.268 | 0.010 | 0.0 | 0.268 | 1 | 1 | 0.000 | 1.000 | 0.110 | 0.002 | 2.439 | 0.110 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 46.744 | 0.000 | 0.0 | 0.047 | -1 | 5 | 0.820 | 0.820 | 4.538 | 0.030 | 10.300 | 0.069 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.237 | 0.021 | 0.0 | 0.237 | -1 | 5 | 1.000 | 1.000 | 0.111 | 0.002 | 2.142 | 0.195 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 35.229 | 0.000 | 0.0 | 0.035 | -1 | 1 | 0.712 | 0.719 | 4.616 | 0.073 | 7.632 | 0.121 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.228 | 0.014 | 0.0 | 0.228 | -1 | 1 | 0.000 | 1.000 | 0.109 | 0.003 | 2.088 | 0.137 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 31.417 | 0.000 | 0.0 | 0.031 | 1 | 5 | 0.820 | 0.949 | 4.674 | 0.020 | 6.721 | 0.029 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.258 | 0.005 | 0.0 | 0.258 | 1 | 5 | 1.000 | 1.000 | 0.108 | 0.002 | 2.377 | 0.068 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 47.181 | 0.000 | 0.0 | 0.047 | -1 | 100 | 0.922 | 0.719 | 4.564 | 0.029 | 10.339 | 0.065 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.229 | 0.028 | 0.0 | 0.229 | -1 | 100 | 1.000 | 1.000 | 0.110 | 0.004 | 2.080 | 0.260 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 31.331 | 0.000 | 0.0 | 0.031 | 1 | 100 | 0.922 | 0.820 | 4.596 | 0.040 | 6.817 | 0.060 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.263 | 0.006 | 0.0 | 0.263 | 1 | 100 | 1.000 | 1.000 | 0.118 | 0.007 | 2.223 | 0.140 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 13.147 | 0.193 | 0.0 | 0.013 | 1 | 1 | 0.972 | 0.984 | 1.096 | 0.008 | 12.000 | 0.198 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.021 | 0.003 | 0.0 | 0.021 | 1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 3.820 | 0.623 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 36.539 | 0.000 | 0.0 | 0.037 | -1 | 5 | 0.984 | 0.983 | 1.022 | 0.009 | 35.755 | 0.313 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.034 | 0.004 | 0.0 | 0.034 | -1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 6.685 | 0.862 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 28.329 | 0.182 | 0.0 | 0.028 | -1 | 1 | 0.972 | 0.970 | 1.019 | 0.016 | 27.790 | 0.467 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.025 | 0.003 | 0.0 | 0.025 | -1 | 1 | 1.000 | 1.000 | 0.005 | 0.001 | 4.671 | 0.709 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 21.393 | 0.217 | 0.0 | 0.021 | 1 | 5 | 0.984 | 0.984 | 1.102 | 0.016 | 19.405 | 0.341 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.024 | 0.001 | 0.0 | 0.024 | 1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 4.721 | 0.336 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 34.551 | 0.000 | 0.0 | 0.035 | -1 | 100 | 0.984 | 0.970 | 1.017 | 0.015 | 33.959 | 0.490 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.032 | 0.003 | 0.0 | 0.032 | -1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 6.730 | 0.728 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 20.482 | 0.436 | 0.0 | 0.020 | 1 | 100 | 0.984 | 0.983 | 1.013 | 0.023 | 20.224 | 0.632 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.022 | 0.001 | 0.0 | 0.022 | 1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 4.361 | 0.311 | See | See |
KNeighborsClassifier_kd_tree: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.569 | 0.0 | 0.022 | 0.0 | -1 | 1 | NaN | NaN | 0.898 | 0.0 | 3.976 | 0.0 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.262 | 0.0 | 0.025 | 0.0 | 1 | 1 | NaN | NaN | 0.844 | 0.0 | 3.863 | 0.0 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.127 | 0.0 | 0.026 | 0.0 | 1 | 5 | NaN | NaN | 0.908 | 0.0 | 3.444 | 0.0 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.274 | 0.0 | 0.024 | 0.0 | 1 | 100 | NaN | NaN | 0.843 | 0.0 | 3.885 | 0.0 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.168 | 0.0 | 0.025 | 0.0 | -1 | 5 | NaN | NaN | 0.894 | 0.0 | 3.543 | 0.0 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 3.321 | 0.0 | 0.024 | 0.0 | -1 | 100 | NaN | NaN | 0.840 | 0.0 | 3.954 | 0.0 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.804 | 0.0 | 0.020 | 0.0 | -1 | 1 | NaN | NaN | 0.548 | 0.0 | 1.469 | 0.0 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.877 | 0.0 | 0.018 | 0.0 | 1 | 1 | NaN | NaN | 0.534 | 0.0 | 1.641 | 0.0 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.900 | 0.0 | 0.018 | 0.0 | 1 | 5 | NaN | NaN | 0.554 | 0.0 | 1.625 | 0.0 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.946 | 0.0 | 0.017 | 0.0 | 1 | 100 | NaN | NaN | 0.576 | 0.0 | 1.643 | 0.0 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.921 | 0.0 | 0.017 | 0.0 | -1 | 5 | NaN | NaN | 0.590 | 0.0 | 1.562 | 0.0 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.930 | 0.0 | 0.017 | 0.0 | -1 | 100 | NaN | NaN | 0.533 | 0.0 | 1.746 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.486 | 0.010 | 0.0 | 0.000 | -1 | 1 | 0.963 | 0.972 | 0.256 | 0.008 | 1.900 | 0.073 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.0 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 10.807 | 4.814 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.835 | 0.018 | 0.0 | 0.001 | 1 | 1 | 0.963 | 0.972 | 0.271 | 0.013 | 3.084 | 0.159 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.0 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 2.706 | 1.362 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 1.620 | 0.041 | 0.0 | 0.002 | 1 | 5 | 0.973 | 0.947 | 0.142 | 0.012 | 11.416 | 1.004 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.0 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 4.268 | 1.919 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 5.394 | 0.125 | 0.0 | 0.005 | 1 | 100 | 0.975 | 0.974 | 0.771 | 0.013 | 6.994 | 0.199 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.0 | 0.003 | 1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 4.534 | 1.966 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.853 | 0.018 | 0.0 | 0.001 | -1 | 5 | 0.973 | 0.974 | 0.781 | 0.029 | 1.093 | 0.047 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.0 | 0.003 | -1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 4.784 | 1.858 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 2.850 | 0.026 | 0.0 | 0.003 | -1 | 100 | 0.975 | 0.947 | 0.132 | 0.003 | 21.582 | 0.501 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.005 | 0.001 | 0.0 | 0.005 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 18.856 | 9.121 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.036 | 0.002 | 0.0 | 0.000 | -1 | 1 | 0.967 | 0.984 | 0.001 | 0.000 | 26.665 | 8.483 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.0 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 14.704 | 8.398 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.034 | 0.002 | 0.0 | 0.000 | 1 | 1 | 0.967 | 0.984 | 0.001 | 0.001 | 22.795 | 8.305 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.0 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 4.229 | 2.494 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.037 | 0.001 | 0.0 | 0.000 | 1 | 5 | 0.977 | 0.981 | 0.001 | 0.000 | 41.227 | 13.681 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.0 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 4.464 | 2.777 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.071 | 0.002 | 0.0 | 0.000 | 1 | 100 | 0.979 | 0.983 | 0.008 | 0.001 | 8.616 | 0.603 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.001 | 0.000 | 0.0 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 4.586 | 1.924 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.041 | 0.002 | 0.0 | 0.000 | -1 | 5 | 0.977 | 0.983 | 0.008 | 0.001 | 4.983 | 0.495 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.000 | 0.0 | 0.003 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 15.535 | 6.701 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.062 | 0.003 | 0.0 | 0.000 | -1 | 100 | 0.979 | 0.981 | 0.001 | 0.000 | 59.872 | 18.044 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 2 | 0 | 42 | sklearn.datasets.make_classification | NaN | 0.003 | 0.001 | 0.0 | 0.003 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 18.539 | 11.564 | See | See |
KMeans_tall: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.764 | 0.0 | 0.628 | 0.0 | k-means++ | NaN | 30 | NaN | 0.342 | 0.0 | 2.234 | 0.0 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.610 | 0.0 | 0.787 | 0.0 | random | NaN | 30 | NaN | 0.369 | 0.0 | 1.654 | 0.0 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 9.151 | 0.0 | 2.623 | 0.0 | k-means++ | NaN | 30 | NaN | 4.243 | 0.0 | 2.157 | 0.0 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 8.037 | 0.0 | 2.986 | 0.0 | random | NaN | 30 | NaN | 4.492 | 0.0 | 1.789 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.255 | 0.000 | k-means++ | 0.000 | 30 | 0.001 | 0.0 | 0.0 | 7.734 | 3.374 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.000 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 8.094 | 3.042 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.267 | 0.000 | random | 0.000 | 30 | 0.001 | 0.0 | 0.0 | 7.010 | 2.154 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.000 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 9.557 | 3.981 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 11.796 | 0.000 | k-means++ | 0.001 | 30 | 0.002 | 0.0 | 0.0 | 6.049 | 1.919 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.013 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 9.370 | 5.082 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 11.758 | 0.000 | random | 0.002 | 30 | 0.003 | 0.0 | 0.0 | 5.657 | 2.354 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 30 | 0.002 | 0.0 | 0.013 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 9.449 | 5.307 | See | See |
KMeans_short: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.325 | 0.0 | 0.010 | 0.0 | k-means++ | NaN | 20 | NaN | 0.056 | 0.0 | 5.778 | 0.0 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.106 | 0.0 | 0.030 | 0.0 | random | NaN | 20 | NaN | 0.191 | 0.0 | 0.554 | 0.0 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 1.188 | 0.0 | 0.135 | 0.0 | k-means++ | NaN | 20 | NaN | 0.308 | 0.0 | 3.860 | 0.0 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.362 | 0.0 | 0.442 | 0.0 | random | NaN | 20 | NaN | 0.664 | 0.0 | 0.545 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_random_state | dataset_cluster_std | dataset_centers | dataset_sample_generator | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.003 | 0.001 | 0.122 | 0.000 | k-means++ | 0.004 | 20 | -0.001 | 0.001 | 0.0 | 3.284 | 1.208 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.000 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.531 | 4.667 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.138 | 0.000 | random | 0.002 | 20 | 0.000 | 0.001 | 0.0 | 2.738 | 0.617 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 42 | 20.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.000 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 7.592 | 5.510 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.004 | 0.000 | 4.494 | 0.000 | k-means++ | 0.309 | 20 | 0.315 | 0.002 | 0.0 | 2.097 | 0.321 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.008 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.133 | 3.540 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.004 | 0.000 | 4.515 | 0.000 | random | 0.286 | 20 | 0.359 | 0.002 | 0.0 | 2.121 | 0.303 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 42 | 13.0 | 200 | sklearn.datasets.make_blobs | 20 | 0.002 | 0.000 | 0.008 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.059 | 2.988 | See | See |
LogisticRegression: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_informative | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 17.673 | 0.0 | [-0.06676297] | 0.000 | NaN | NaN | NaN | NaN | NaN | 3.203 | 0.0 | 5.517 | 0.0 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [26] | 1.400 | 0.0 | [1.48531349] | 0.001 | NaN | NaN | NaN | NaN | NaN | 1.330 | 0.0 | 1.053 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_classes | dataset_n_informative | dataset_n_redundant | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 0.000 | 0.0 | [39.59390512] | 0.0 | NaN | NaN | NaN | NaN | 0.519 | 0.000 | 0.000 | 0.837 | 0.450 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [20] | 0.000 | 0.0 | [0.13153492] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.000 | 0.000 | 0.426 | 0.312 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [26] | 0.003 | 0.0 | [81.61674292] | 0.0 | NaN | NaN | NaN | NaN | 0.310 | 0.004 | 0.001 | 0.570 | 0.094 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 5 | 5 | 0 | 42 | sklearn.datasets.make_classification | [26] | 0.000 | 0.0 | [13.63657223] | 0.0 | NaN | NaN | NaN | NaN | 0.000 | 0.001 | 0.000 | 0.165 | 0.078 | See | See |
Ridge: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_informative | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.342 | 0.0 | 0.234 | 0.0 | NaN | NaN | NaN | 0.335 | 0.0 | 1.022 | 0.0 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 1.902 | 0.0 | 0.421 | 0.0 | NaN | NaN | NaN | 0.438 | 0.0 | 4.347 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | dataset_n_informative | dataset_random_state | dataset_sample_generator | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.013 | 0.001 | 6.301 | 0.0 | NaN | NaN | 0.104 | 0.022 | 0.001 | 0.568 | 0.036 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.000 | 0.000 | 0.566 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.775 | 0.469 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.000 | 0.000 | 4.430 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.000 | 0.654 | 0.371 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 10 | 42 | sklearn.datasets.make_regression | NaN | 0.000 | 0.000 | 0.008 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.575 | 0.555 | See | See |